Clinical applications of artificial intelligence in robotic surgery

Knudsen, J. Everett; Ghaffar, Umar; Ma, Runzhuo; Hung, Andrew J.

doi:10.1007/s11701-024-01867-0

Cited by 8 publications

(2 citation statements)

References 45 publications

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“…Research in these fields has led to the development of increasingly complex and powerful machine learning models, culminating with the development of deep learning, which has revolutionized the field of AI by attaining advanced capabilities in tasks such as image recognition and natural language processing by combining the use of sophisticated algorithms, large datasets, and powerful computational resources. These innovations are bound to affect the field of surgery ( 2 , 3 ).…”

Section: Introductionmentioning

confidence: 99%

Current and future applications of artificial intelligence in surgery: implications for clinical practice and research

Morris,

Fiocco,

Caneva

et al. 2024

Front. Surg.

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Surgeons are skilled at making complex decisions over invasive procedures that can save lives and alleviate pain and avoid complications in patients. The knowledge to make these decisions is accumulated over years of schooling and practice. Their experience is in turn shared with others, also via peer-reviewed articles, which get published in larger and larger amounts every year. In this work, we review the literature related to the use of Artificial Intelligence (AI) in surgery. We focus on what is currently available and what is likely to come in the near future in both clinical care and research. We show that AI has the potential to be a key tool to elevate the effectiveness of training and decision-making in surgery and the discovery of relevant and valid scientific knowledge in the surgical domain. We also address concerns about AI technology, including the inability for users to interpret algorithms as well as incorrect predictions. A better understanding of AI will allow surgeons to use new tools wisely for the benefit of their patients.

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Section: Introductionmentioning

confidence: 99%

Current and future applications of artificial intelligence in surgery: implications for clinical practice and research

Morris,

Fiocco,

Caneva

et al. 2024

Front. Surg.

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“…A procedure exemplifying the use of AI in surgical assistance is the deployment of the da Vinci Robotic Surgical System. This system operates on a "master-slave" principle, where a human surgeon performs all surgical maneuvers within a console setup [ 11 ]. These maneuvers are then conveyed to the robotic arms positioned at the patient's surgical site.…”

Section: Introductionmentioning

confidence: 99%

A Comparison of Diagnostic and Immunohistochemical Workup and Literature Review Capabilities of Online Artificial Intelligence Assistance Models in Pathology

Dougan,

Patel,

Bardarov

2024

Cureus

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Artificial intelligence (AI) is a suite of technologies that enables computers to learn and interpret information like human cognition. It has found applications across various fields, including healthcare, agriculture, astronomy, navigation, and robotics. Within healthcare, AI has the potential to enhance diagnostic accuracy, facilitate drug research, and automate patient experiences. This comparative study focuses on the proficiency of AI in generating accurate differential diagnoses in the field of pathology. Six medical vignettes were crafted, and each scenario was then input into three different AI platforms. The pathologist reviewed and determined the most accurate AI model.

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Artificial intelligence-aided ultrasound imaging in hepatopancreatobiliary surgery: where are we now?

Bektaş,

Chia,

Burchell

et al. 2024

Surg Endosc

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Background Artificial intelligence (AI) models have been applied in various medical imaging modalities and surgical disciplines, however the current status and progress of ultrasound-based AI models within hepatopancreatobiliary surgery have not been evaluated in literature. Therefore, this review aimed to provide an overview of ultrasound-based AI models used for hepatopancreatobiliary surgery, evaluating current advancements, validation, and predictive accuracies. Method Databases PubMed, EMBASE, Cochrane, and Web of Science were searched for studies using AI models on ultrasound for patients undergoing hepatopancreatobiliary surgery. To be eligible for inclusion, studies needed to apply AI methods on ultrasound imaging for patients undergoing hepatopancreatobiliary surgery. The Probast risk of bias tool was used to evaluate the methodological quality of AI methods. Results AI models have been primarily used within hepatopancreatobiliary surgery, to predict tumor recurrence, differentiate between tumoral tissues, and identify lesions during ultrasound imaging. Most studies have combined radiomics with convolutional neural networks, with AUCs up to 0.98. Conclusion Ultrasound-based AI models have demonstrated promising accuracies in predicting early tumoral recurrence and even differentiating between tumoral tissue types during and after hepatopancreatobiliary surgery. However, prospective studies are required to evaluate if these results will remain consistent and externally valid. Graphical abstract

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Clinical applications of artificial intelligence in robotic surgery

Cited by 8 publications

References 45 publications

Current and future applications of artificial intelligence in surgery: implications for clinical practice and research

Current and future applications of artificial intelligence in surgery: implications for clinical practice and research

A Comparison of Diagnostic and Immunohistochemical Workup and Literature Review Capabilities of Online Artificial Intelligence Assistance Models in Pathology

Artificial intelligence-aided ultrasound imaging in hepatopancreatobiliary surgery: where are we now?

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